Courses

I recently discovered two great tools for easily creating interactive coding environments without installing a thing. These tools facilitate sharing of code in multiple languages and are wonderful resources for demonstrating programming concepts when teaching a course. Binder The first tool is called Binder, is open-source and was released in 2017. It is awesome because it allows data scientists to share their work in Python , R or Julia in a reproducible manner. Binder can be configured for Python (Anaconda or pip environment) and R (using RStudio and/or Shiny). Multiple user interfaces can be specified. For example, for Python we can use a terminal or Jupyter notebook in the repo. ...

For upskilling on AI/ML, I prefer taking a top-down approach i.e. starting with high level concepts then proceeding to more foundational topics (read: delve more into the theory) . I liked taking the breadth-first approach (rather than a depth-first approach) to initially understand AI/ML. Once I had a solid foundation, I easily pivoted to learning a specific topic, like masked regional CNNs, for building expertise through real-world experience. I took multiple courses and read several authors at the same time. You want to find the right sources of information for you and there are so many options out there, so explore. Sometimes I need to read or watch something a few times from different folks before it just clicks. This ultimately accelerated my learning of concepts. Completion of courses should not be the ultimate goal as some courses cover trivial topics and others go too deep into other topics. ...